Course abstract:

The purpose of visualization is to allow the user to gain insight into data by representing the data through images. As data can originate from various sources, e.g., medical CT scanners, weather simulation or stock trading logs, different visualization metaphors are needed to represent the data in a meaningful way. Traditionally, visualization is split into two subfields: information visualization and scientific visualization. While information visualization deals with the representation of abstract data often stored in spreadsheets, scientific visualization deals with data which has an inherent spatial component. Within this course we will focus on scientific visualization and learn how to transform spatial data - which might also have a temporal component - into meaningful visual representations. We will learn how the image representations generated through this transformation process can be both, expressive and - in order to allow interactive visualization - also be generated rapidly.

The course starts with an introduction to visualization, before it focuses on the basics of visualization, such as the visualization pipeline, data representations and fundamental algorithms for scalar and vector visualization. Volume rendering, which exploits besides color also transparency, is covered in an extra block, as it is an essential part of scientific visualization. Finally, perceptual and cognitive aspects are reviewed as knowledge about the human visual system is essential in order to generate expressive visualizations.

In this lab, you will visualize both scalar and vector data. The scalar you created in the previous lab will be visualized using iso-surfaces. The vector data will be visualized using for instance stream lines.